This study was designed to obtain information regarding
community, neighborhood, local government, and community-based
activities in an effort to discover ways of reducing poverty in the
Northwestern states of Idaho, Iowa, Minnesota, Montana, North Dakota,
Oregon, South Dakota, and Washington. Respondents were asked a series
of questions relating to their attitudes toward their place of
residence. They were asked how long they had lived at their current
place of residence, what was the be... (more info)

This study was designed to obtain information regarding
community, neighborhood, local government, and community-based
activities in an effort to discover ways of reducing poverty in the
Northwestern states of Idaho, Iowa, Minnesota, Montana, North Dakota,
Oregon, South Dakota, and Washington. Respondents were asked a series
of questions relating to their attitudes toward their place of
residence. They were asked how long they had lived at their current
place of residence, what was the best thing about living there, and
what changes they would make. Respondents were asked more specific
questions about their immediate community and neighborhood such as
whether they felt safe walking around during the day and at night,
whether there were job opportunities, and how they perceived race
relations and living conditions in their community. They were asked
whether or not people in their community shared similar values as well
as what sorts of attitudes people in their community had. For example,
respondents were asked whether there was a sense of belonging, hope,
worry, pride, anger, or boredom among members of their community. They
were also asked about the importance of feeling like a member of a
community and about their personal relationships with fellow
neighbors. Other questions concerned their involvement in public
affairs, from what sources they received their news, whether or not
they trusted those news sources, and with what frequency they read the
newspaper. Respondents were asked if they felt the government had the
greatest responsibility in caring for citizens and whether the
government cared more about individuals or larger interests.
Respondents were also asked about their social activism such as
volunteer work, donating blood, and attending government meetings.
Other questions asked about their voting history, as well as their
involvement with local church, sports, civic, and fraternal
organizations. Respondents were asked about their geographic location
including state, county, and town, whether their place of residence
was considered urban or rural, and whether or not they lived near an
Indian reservation. The survey also collected general information on
the respondents such as gender, education, marital status, employment
status, and income.

To protect respondent privacy, certain geographic variables belonging to the original dataset are restricted from general dissemination. Users interested in obtaining these data must complete an Agreement for the Use of Confidential Data, specify the reasons for the request, and obtain IRB approval or notice of exemption for their research. Apply for access to these data through the ICPSR Restricted Data Contract Portal, which can be accessed via the study home page.

Study Description

Citation

University of Oregon. Oregon Survey Research Laboratory, and Northwest Area Foundation. Northwest Area Foundation Social Indicators Survey, September-December 2003. ICPSR04694-v1. Ann Arbor, MI: Inter-university Consortium for Political and Social Research [distributor], 2007-07-10. http://doi.org/10.3886/ICPSR04694.v1

Universe:
Adults 18 and older living in the Northwestern region of
the United States including the following states: Idaho, Iowa,
Minnesota, Montana, North Dakota, Oregon, South Dakota, and
Washington.

Data Types:
survey data

Data Collection Notes:

(1) More information about the Northwest Area
Foundation can be found online at http://www.nwaf.org/. (2) Responses
to open-ended questions can be found in the codebook. (3) In the
banner tables, the second category for the variable HH income (INCOME)
category should read "$18,000-$25,000."

Methodology

Sample:
The final sample of 8,381 respondents was taken from an
initial screening of 96,628 phone calls.

Weight:

Weights were calculated on two levels (state and region)
using three demographic variables (age, sex, and household size).
State weights are appropriate for analyses restricted to individual
states. Region weights are appropriate for analyses of all eight
states combined. If other combinations of states are required, then
additional weights should be calculated. Since no one source provided
all the weighting data required, two data sources were consulted in
the calculation of the weights. Data on household size were taken from
the 2000 United States Census (table available in Summary File 1 at
http://www.census.gov). Data on age and sex were obtained from the
Census Bureau's Population Estimates Program's 2002 population
estimates (available at
http://www.census.gov/popest/archives/2000s/vintage_2002/).

State-level weights (variable name WTSTATE) were calculated by
multiplying the individual weight variables:

WTSTATE: Age Weight x Sex Weight x Household Size Weight.

To account for the difference in state population sizes and each
state's proportional contribution to the regional population, an
additional weight was added to the region-level weighting equation
(variable name WTREGION). This weight captured the percentage of the
regional population that resides in the respondent's state, and data
from the Census Bureau's Population Estimates Program's 2002
population estimates were used in the development of this weight.

The region-level weights were calculated by multiplying the
individual-level weight variables:

For cases that were missing data on one or more of the weighting
variables, partial weights were calculated for cases using the data
that were available. Data for two of the three weighting variables
were available for 25 of the 28 cases excluded by the first missing
data strategy. For these cases, the available data were multiplied and
substituted for the zero value used in the first missing data
strategy. Of the three remaining cases, two had data for one of the
three weighting variables. For these cases, the weight for that
individual variable was substituted for the zero value used in the
first missing data strategy. Finally, a single case did not have data
for any of the weighting variables, and in this case the zero weight
was preserved.